Springer Iranian Journal of Science 2731-8095 36 2 2012 05 01 A weighted pairwise likelihood approach to multivariate AR(1) models 137 145 2064 10.22099/ijsts.2012.2064 EN Kazemi M. R. Department of Statistics, College of Sciences, Shiraz University, Shiraz 71454, Iran A. R. Nematollahi Department of Statistics, College of Sciences, Shiraz University, Shiraz 71454, Iran Journal Article 2011 06 26 In this paper, the use of weighted pairwise likelihood instead of the full likelihood in estimating the parameters of the multivariate AR(1) is investigated. A closed formula for typical elements of the Godambe information<br />(sandwich information) is presented. Some efficiency calculations are also given to discuss the feasibility and<br />computational advantages of the weighted pairwise likelihood approach relative to the full likelihood approach. https://ijsts.shirazu.ac.ir/article_2064_f058fdf0c083f762aedbf364e9c28f88.pdf